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[Previously saved workspace restored]

> source("../../R/mixture_irt_md.R")
aroma.light v3.22.0 (2021-05-19) successfully loaded. See ?aroma.light for help.
> 
> library(tidyverse)
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
✔ ggplot2 3.3.5     ✔ purrr   0.3.4
✔ tibble  3.1.5     ✔ dplyr   1.0.7
✔ tidyr   1.1.3     ✔ stringr 1.4.0
✔ readr   1.4.0     ✔ forcats 0.5.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
> library(multidplyr)
> library(dplyr, warn.conflicts = FALSE)
> library(tictoc)
> 
> 
> set.seed(123)
> 
> # Pull in mega-survey dataset and arrange into long format
> if (!exists("long_data")) {
+   load("../../../Code/bigsurveys_recoded_plus_estimates4.RData")
+   long_data <- data %>%
+     select(source, respondent, pid7, cces2006_minimumwage:cces2017_buyamerican) %>%
+     select(-cces2012_immigration5, -cces2012_immigration6) %>% # Drop redundant immigration items in CCES2012
+     pivot_longer( cols = cces2006_minimumwage:cces2017_buyamerican,
+                   names_to="item",
+                   values_to="choice") %>%
+     filter(!is.na(choice)) 
+ }
> glimpse(long_data)
Rows: 12,398,379
Columns: 5
$ source     <chr> "CCES_2006", "CCES_2006", "CCES_2006", "CCES_2006", "CCES_2…
$ respondent <dbl> 1000035, 1000035, 1000035, 1000035, 1000035, 1000035, 10000…
$ pid7       <chr> "1", "1", "1", "1", "1", "1", "1", "1", "1", "2", "2", "2",…
$ item       <chr> "cces2006_minimumwage", "cces2006_abortion", "cces2006_envi…
$ choice     <dbl> 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0,…
> 
> 
> # Do a little checking of the sample sizes and number of items per survey
> long_data %>% 
+   filter(source %in% sprintf("CCES_%i", 2012:2018)) %>%
+   group_by(source, item) %>%
+   mutate(n=n()) %>%
+   filter(n>4999) %>% # Drop the "module" items ask of fewer respondents
+   group_by(source) %>%
+   mutate(source_n = length(unique(respondent))) %>%
+   group_by(source, item) %>%
+   summarize(n=n(), 
+             source_n=source_n[1], 
+             .groups="drop") %>%
+   group_by(source) %>%
+   summarize(n_items = n(),
+             source_n = source_n[1],
+             min_responses = min(n),
+             max_responses = max(n))
# A tibble: 7 × 5
  source    n_items source_n min_responses max_responses
  <chr>       <int>    <int>         <int>         <int>
1 CCES_2012      19    54535         48758         54535
2 CCES_2013      22    16400         15827         16400
3 CCES_2014      32    56200         54140         56200
4 CCES_2015      33    14250         13560         14250
5 CCES_2016      32    64600         13155         64600
6 CCES_2017      31    18200         17811         18200
7 CCES_2018      35    59999         51483         59937
> 
> 
> # Global container to hold results
> all_res <- list()
> 
> # fuction it model to each Survey dataset
> fit_em_mix_irt_2d <- function(long_dat, ndim=1, ...) {
+   tic()
+   cat(sprintf("Working on %s...\n", long_dat$source[1]))
+   wide_dat <- long_dat %>%
+     group_by(source, item) %>%
+     filter(n() > 4999) %>%              # Drop "module" items (items asked of fewer than 5k respondents)
+     group_by(source, respondent) %>%
+     #filter(n() > 18) %>%               # Drop respondents answering fewer than 19 items.
+     pivot_wider(id_cols = c("source", "respondent", "pid7"),
+                 names_from=item,
+                 values_from=choice) %>%
+     ungroup()
+   item_summary <- tibble(item = names(wide_dat %>% select(-source, -respondent, -pid7)),
+                          number_responses = wide_dat %>% select(-source, -respondent, -pid7) %>% 
+                            apply(2,function(x) sum(!is.na(x))),
+                          proportion_ones  = wide_dat %>% select(-source, -respondent, -pid7) %>% 
+                            apply(2,function(x) sum(x==1, na.rm=TRUE))/number_responses,
+                          invalid_responses = wide_dat %>% select(-source, -respondent, -pid7) %>% 
+                            apply(2,function(x) sum(!(is.na(x) | x %in% 0:1)))) %>%
+     mutate(item_number = 1:n()) %>%
+     select(item_number, everything())
+   cat("Item summary:\n")
+   print(item_summary)
+   cat("\n")
+   res <- em_mix_irt(wide_dat %>% select(-source, -respondent, -pid7) %>% as.matrix(),
+                     ndim=ndim, ...)
+   res$item_summary <- item_summary
+   # Set polarity for the first recovered IRT dimension
+   flip_sign <- sign(cor(as.numeric(wide_dat$pid7),
+                         res$irt$x[,1],
+                         use="pairwise.complete.obs"))
+   all_res[[wide_dat$source[[1]]]] <<- res
+   wide_dat <- wide_dat %>%
+     mutate(lk1 = res$irt$lk,
+            lk2 = res$ivp$lk,
+            w1  = res$w[,1],
+            w2  = res$w[,2],
+            w3  = res$w[,3])
+   for (j in 1:ndim) {
+     wide_dat[[sprintf("x%i", j)]] <- ifelse(j==1, flip_sign, 1)*res$irt$x[,j] 
+   }
+   toc()
+   wide_dat
+ }
> 
> # Run em_mix_irt on each survey...
> resulting_data <- long_data %>% 
+   filter(source %in% sprintf("CCES_%i", 2012:2018)) %>%
+   group_by(source) %>%
+   do(fit_em_mix_irt_2d(., ndim=2, xsamp=5000, iters=100, irt_iters=100, w_alpha=c(100,1,1))) %>%
+   bind_rows() 
Working on CCES_2012...
Item summary:
# A tibble: 19 × 5
   item_number item                       number_responses proportion_ones invalid_respons…
         <int> <chr>                                 <int>           <dbl>            <int>
 1           1 cces2006_climatechange                54371           0.427                0
 2           2 cces2006_abortion                     54115           0.366                0
 3           3 cces2006_environment                  54300           0.702                0
 4           4 cces2006_affirmativeaction            54297           0.609                0
 5           5 naes2000_gaysmilitary                 53689           0.323                0
 6           6 naes2004_stategaymarriage             53947           0.479                0
 7           7 cces2012_housebudgetplan              53240           0.187                0
 8           8 cces2012_simpsonbowles                53657           0.487                0
 9           9 cces2012_middleclasstaxcut            51821           0.614                0
10          10 cces2012_bushtaxcuts                  51755           0.267                0
11          11 cces2012_birthcontrol                 53340           0.392                0
12          12 cces2012_koreafreetrade               52265           0.509                0
13          13 cces2012_repeal.aca                   52172           0.446                0
14          14 cces2012_keystonepipeline             48758           0.734                0
15          15 cces2012_supportaca                   53766           0.431                0
16          16 cces2010_immigration2                 54535           0.536                0
17          17 cces2010_immigration4                 54535           0.565                0
18          18 cces2010_immigration5                 54535           0.400                0
19          19 cces2010_immigration1                 54535           0.630                0

Outer iteration: 1
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Group probs = (0.9710, 0.0137, 0.0154)

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Group probs = (0.6469, 0.2954, 0.0577)

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Group probs = (0.6257, 0.3097, 0.0646)

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Group probs = (0.6240, 0.3108, 0.0652)

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Group probs = (0.6245, 0.3100, 0.0655)

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Group probs = (0.6149, 0.3144, 0.0706)

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Group probs = (0.6165, 0.3125, 0.0710)

10194.199 sec elapsed
Working on CCES_2013...
Item summary:
# A tibble: 22 × 5
   item_number item                       number_responses proportion_ones invalid_respons…
         <int> <chr>                                 <int>           <dbl>            <int>
 1           1 cces2006_climatechange                16341           0.423                0
 2           2 cces2006_environment                  16350           0.691                0
 3           3 cces2006_affirmativeaction            16318           0.622                0
 4           4 naes2004_assaultweapons               16200           0.366                0
 5           5 cces2012_simpsonbowles                16193           0.343                0
 6           6 cces2012_repeal.aca                   15827           0.537                0
 7           7 cces2012_keystonepipeline             15899           0.686                0
 8           8 cces2010_immigration2                 16400           0.532                0
 9           9 cces2010_immigration4                 16400           0.535                0
10          10 cces2010_immigration5                 16400           0.366                0
# … with 12 more rows

Outer iteration: 1
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Group probs = (0.9685, 0.0143, 0.0172)

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Group probs = (0.9472, 0.0267, 0.0260)

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Group probs = (0.9214, 0.0472, 0.0314)

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Group probs = (0.8827, 0.0776, 0.0397)

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Group probs = (0.7676, 0.1892, 0.0432)

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Group probs = (0.7598, 0.1989, 0.0413)

Outer iteration: 31
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Group probs = (0.7547, 0.2048, 0.0405)

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Group probs = (0.7514, 0.2090, 0.0395)

Outer iteration: 33
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Outer iteration: 34
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Group probs = (0.7403, 0.2217, 0.0381)

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Group probs = (0.7343, 0.2281, 0.0376)

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Group probs = (0.7198, 0.2436, 0.0367)

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Group probs = (0.7152, 0.2484, 0.0364)

Outer iteration: 40
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Outer iteration: 46
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Group probs = (0.6492, 0.2957, 0.0552)

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Group probs = (0.6464, 0.2976, 0.0560)

Outer iteration: 68
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Outer iteration: 69
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Group probs = (0.6447, 0.2973, 0.0580)

Outer iteration: 70
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Group probs = (0.6432, 0.2977, 0.0591)

Outer iteration: 71
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Group probs = (0.6416, 0.2982, 0.0602)

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Group probs = (0.6415, 0.2975, 0.0610)

Outer iteration: 73
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Group probs = (0.6389, 0.2993, 0.0619)

Outer iteration: 74
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Group probs = (0.6361, 0.3011, 0.0627)

Outer iteration: 75
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Group probs = (0.6345, 0.3008, 0.0647)

Outer iteration: 77
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Iteration: 100 (-67315.3935, 0.0078)
Group probs = (0.6197, 0.3059, 0.0743)

3139.397 sec elapsed
Working on CCES_2014...
Item summary:
# A tibble: 32 × 5
   item_number item                       number_responses proportion_ones invalid_respons…
         <int> <chr>                                 <int>           <dbl>            <int>
 1           1 cces2006_affirmativeaction            56003           0.602                0
 2           2 naes2004_stategaymarriage             55670           0.411                0
 3           3 naes2004_assaultweapons               55732           0.355                0
 4           4 cces2012_housebudgetplan              55326           0.220                0
 5           5 cces2012_simpsonbowles                55306           0.316                0
 6           6 cces2012_middleclasstaxcut            55219           0.493                0
 7           7 cces2012_bushtaxcuts                  54140           0.267                0
 8           8 cces2012_birthcontrol                 55157           0.398                0
 9           9 cces2012_koreafreetrade               54905           0.565                0
10          10 cces2012_repeal.aca                   55801           0.511                0
# … with 22 more rows

Outer iteration: 1
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Group probs = (0.9649, 0.0137, 0.0213)

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Group probs = (0.9338, 0.0328, 0.0334)

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Group probs = (0.9027, 0.0577, 0.0396)

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Group probs = (0.8773, 0.0778, 0.0449)

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Group probs = (0.8573, 0.0945, 0.0482)

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Group probs = (0.8398, 0.1099, 0.0503)

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Group probs = (0.8264, 0.1217, 0.0518)

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Group probs = (0.8151, 0.1318, 0.0530)

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Group probs = (0.8069, 0.1392, 0.0539)

Outer iteration: 10
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Group probs = (0.7995, 0.1457, 0.0547)

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Group probs = (0.7940, 0.1508, 0.0553)

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Group probs = (0.7892, 0.1549, 0.0560)

Outer iteration: 13
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Group probs = (0.7857, 0.1582, 0.0560)

Outer iteration: 14
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Group probs = (0.7825, 0.1612, 0.0563)

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Group probs = (0.7795, 0.1639, 0.0566)

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Group probs = (0.7675, 0.1749, 0.0577)

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16409.218 sec elapsed
Working on CCES_2015...
Item summary:
# A tibble: 33 × 5
   item_number item            number_responses proportion_ones invalid_respons…
         <int> <chr>                      <int>           <dbl>            <int>
 1           1 naes2004_state…            14089          0.415                 0
 2           2 naes2004_assau…            14155          0.368                 0
 3           3 cces2012_repea…            14047          0.561                 0
 4           4 cces2012_keyst…            13560          0.576                 0
 5           5 cces2010_immig…            14250          0.498                 0
 6           6 cces2010_immig…            14250          0.533                 0
 7           7 cces2010_immig…            14250          0.354                 0
 8           8 cces2010_immig…            14250          0.589                 0
 9           9 cces2013_viole…            14110          0.0794                0
10          10 cces2013_gunsb…            14174          0.130                 0
# … with 23 more rows

Outer iteration: 1
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Group probs = (0.9709, 0.0106, 0.0185)

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Iteration: 80 (-172601.9105, 0.2982)
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Iteration: 100 (-172485.8322, 0.2695)
Group probs = (0.9584, 0.0152, 0.0265)

Outer iteration: 3
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Iteration: 10 (-168345.0114, 0.2608)
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Iteration: 80 (-168040.5025, 0.1967)
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Iteration: 100 (-167971.7422, 0.1841)
Group probs = (0.9466, 0.0250, 0.0284)

Outer iteration: 4
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Group probs = (0.9338, 0.0390, 0.0272)

Outer iteration: 5
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Group probs = (0.9227, 0.0508, 0.0265)

Outer iteration: 6
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Group probs = (0.9129, 0.0604, 0.0267)

Outer iteration: 7
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Group probs = (0.9030, 0.0690, 0.0280)

Outer iteration: 8
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Group probs = (0.8937, 0.0771, 0.0291)

Outer iteration: 9
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Group probs = (0.8844, 0.0851, 0.0305)

Outer iteration: 10
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Group probs = (0.8755, 0.0928, 0.0318)

Outer iteration: 11
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Group probs = (0.8668, 0.1000, 0.0332)

Outer iteration: 12
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Group probs = (0.8591, 0.1064, 0.0345)

Outer iteration: 13
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Group probs = (0.8525, 0.1122, 0.0354)

Outer iteration: 14
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Group probs = (0.8473, 0.1165, 0.0362)

Outer iteration: 15
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Group probs = (0.8433, 0.1197, 0.0370)

Outer iteration: 16
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Group probs = (0.8368, 0.1257, 0.0375)

Outer iteration: 17
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Group probs = (0.8312, 0.1305, 0.0383)

Outer iteration: 18
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Group probs = (0.8282, 0.1331, 0.0387)

Outer iteration: 19
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Group probs = (0.8236, 0.1370, 0.0394)

Outer iteration: 20
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Group probs = (0.8191, 0.1409, 0.0401)

Outer iteration: 21
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Group probs = (0.8168, 0.1427, 0.0405)

Outer iteration: 22
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Group probs = (0.8139, 0.1453, 0.0408)

Outer iteration: 23
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Outer iteration: 24
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Group probs = (0.8102, 0.1480, 0.0418)

Outer iteration: 25
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Outer iteration: 26
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Outer iteration: 27
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Outer iteration: 28
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Outer iteration: 29
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Outer iteration: 30
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Outer iteration: 31
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Group probs = (0.7720, 0.1799, 0.0481)

3975.202 sec elapsed
Working on CCES_2016...
Item summary:
# A tibble: 32 × 5
   item_number item            number_responses proportion_ones invalid_respons…
         <int> <chr>                      <int>           <dbl>            <int>
 1           1 naes2004_state…            64125          0.349                 0
 2           2 naes2004_assau…            64151          0.336                 0
 3           3 cces2012_repea…            64509          0.538                 0
 4           4 cces2010_immig…            64600          0.440                 0
 5           5 cces2010_immig…            64600          0.493                 0
 6           6 cces2010_immig…            64600          0.469                 0
 7           7 cces2013_gunsb…            64385          0.0970                0
 8           8 cces2013_gunna…            64217          0.591                 0
 9           9 cces2013_conce…            64223          0.377                 0
10          10 cces2014_abort…            64538          0.383                 0
# … with 22 more rows

Outer iteration: 1
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Group probs = (0.9688, 0.0139, 0.0173)

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Group probs = (0.9502, 0.0242, 0.0255)

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Group probs = (0.8438, 0.1188, 0.0375)

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Group probs = (0.8212, 0.1398, 0.0389)

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Group probs = (0.8001, 0.1595, 0.0403)

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Group probs = (0.7818, 0.1765, 0.0417)

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Group probs = (0.7501, 0.2069, 0.0430)

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Group probs = (0.7357, 0.2202, 0.0441)

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Group probs = (0.7224, 0.2323, 0.0453)

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Outer iteration: 17
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Outer iteration: 21
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Outer iteration: 27
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Group probs = (0.6359, 0.3127, 0.0514)

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Group probs = (0.6374, 0.3115, 0.0511)

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Group probs = (0.6346, 0.3139, 0.0514)

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Group probs = (0.6353, 0.3135, 0.0512)

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Group probs = (0.6343, 0.3143, 0.0514)

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Group probs = (0.6317, 0.3163, 0.0519)

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Group probs = (0.6338, 0.3147, 0.0516)

17332.062 sec elapsed
Working on CCES_2017...
Item summary:
# A tibble: 31 × 5
   item_number item            number_responses proportion_ones invalid_respons…
         <int> <chr>                      <int>           <dbl>            <int>
 1           1 naes2004_assau…            18185          0.300                 0
 2           2 cces2012_repea…            18046          0.445                 0
 3           3 cces2010_immig…            18200          0.440                 0
 4           4 cces2010_immig…            18200          0.426                 0
 5           5 cces2010_immig…            18200          0.279                 0
 6           6 cces2010_immig…            18200          0.506                 0
 7           7 cces2013_gunsb…            18188          0.0939                0
 8           8 cces2013_gunna…            18186          0.546                 0
 9           9 cces2013_conce…            18188          0.375                 0
10          10 cces2014_abort…            18185          0.409                 0
# … with 21 more rows

Outer iteration: 1
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Group probs = (0.9740, 0.0118, 0.0141)

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Group probs = (0.9622, 0.0179, 0.0199)

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Group probs = (0.9482, 0.0282, 0.0237)

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Group probs = (0.9333, 0.0405, 0.0262)

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Group probs = (0.8993, 0.0703, 0.0304)

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Group probs = (0.8839, 0.0844, 0.0317)

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Group probs = (0.8699, 0.0973, 0.0328)

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Group probs = (0.8591, 0.1075, 0.0334)

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Outer iteration: 21
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Group probs = (0.8262, 0.1329, 0.0408)

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Group probs = (0.8213, 0.1371, 0.0416)

4726.02 sec elapsed
Working on CCES_2018...
Item summary:
# A tibble: 35 × 5
   item_number item            number_responses proportion_ones invalid_respons…
         <int> <chr>                      <int>           <dbl>            <int>
 1           1 naes2004_assau…            59564          0.344                 0
 2           2 cces2012_repea…            59926          0.415                 0
 3           3 cces2012_keyst…            59934          0.463                 0
 4           4 cces2013_gunsb…            59717          0.0959                0
 5           5 cces2013_conce…            59590          0.345                 0
 6           6 cces2014_abort…            59901          0.403                 0
 7           7 cces2014_abort…            59898          0.406                 0
 8           8 cces2014_abort…            59914          0.639                 0
 9           9 cces2014_abort…            59937          0.434                 0
10          10 cces2014_feder…            59931          0.439                 0
# … with 25 more rows

Outer iteration: 1
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Group probs = (0.9727, 0.0123, 0.0150)

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Group probs = (0.8213, 0.1509, 0.0278)

Outer iteration: 13
Iteration: 1 (-574985.8299, 1.1751)
Iteration: 10 (-574959.7426, 0.1322)
Iteration: 20 (-574940.8233, 0.1311)
Iteration: 30 (-574922.5353, 0.1297)
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Iteration: 60 (-574869.4601, 0.1251)
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Iteration: 80 (-574835.1857, 0.1221)
Iteration: 90 (-574818.3410, 0.1207)
Iteration: 100 (-574801.6815, 0.1193)
Group probs = (0.8155, 0.1566, 0.0279)

Outer iteration: 14
Iteration: 1 (-568620.2646, 1.0092)
Iteration: 10 (-568591.8455, 0.1160)
Iteration: 20 (-568574.3160, 0.1159)
Iteration: 30 (-568557.6318, 0.1151)
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Iteration: 80 (-568478.4610, 0.1096)
Iteration: 90 (-568463.1949, 0.1085)
Iteration: 100 (-568448.0901, 0.1074)
Group probs = (0.8104, 0.1611, 0.0284)

Outer iteration: 15
Iteration: 1 (-562729.3101, 0.5250)
Iteration: 10 (-562699.0161, 0.1059)
Iteration: 20 (-562682.6566, 0.1055)
Iteration: 30 (-562667.2960, 0.1046)
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Iteration: 80 (-562594.8561, 0.0997)
Iteration: 90 (-562580.8922, 0.0987)
Iteration: 100 (-562567.0717, 0.0978)
Group probs = (0.8082, 0.1632, 0.0287)

Outer iteration: 16
Iteration: 1 (-560154.3824, 0.6190)
Iteration: 10 (-560122.6324, 0.0969)
Iteration: 20 (-560107.0141, 0.0967)
Iteration: 30 (-560092.5683, 0.0960)
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Iteration: 80 (-560024.9902, 0.0919)
Iteration: 90 (-560011.9792, 0.0911)
Iteration: 100 (-559999.1004, 0.0904)
Group probs = (0.8063, 0.1643, 0.0294)

Outer iteration: 17
Iteration: 1 (-557795.8151, 0.4024)
Iteration: 10 (-557766.4276, 0.0897)
Iteration: 20 (-557751.8181, 0.0894)
Iteration: 30 (-557738.3127, 0.0888)
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Iteration: 80 (-557675.1147, 0.0852)
Iteration: 90 (-557662.9417, 0.0845)
Iteration: 100 (-557650.8902, 0.0838)
Group probs = (0.8072, 0.1628, 0.0300)

Outer iteration: 18
Iteration: 1 (-558787.4178, 0.4211)
Iteration: 10 (-558761.9306, 0.0828)
Iteration: 20 (-558748.3744, 0.0827)
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Iteration: 80 (-558676.2366, 0.0793)
Iteration: 90 (-558664.7571, 0.0788)
Iteration: 100 (-558653.3884, 0.0782)
Group probs = (0.8094, 0.1600, 0.0306)

Outer iteration: 19
Iteration: 1 (-561017.3283, 0.3622)
Iteration: 10 (-560998.7332, 0.0772)
Iteration: 20 (-560986.5125, 0.0771)
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Iteration: 90 (-560908.3345, 0.0739)
Iteration: 100 (-560897.6317, 0.0734)
Group probs = (0.8122, 0.1566, 0.0313)

Outer iteration: 20
Iteration: 1 (-563960.2155, 0.3723)
Iteration: 10 (-563945.5044, 0.0723)
Iteration: 20 (-563934.3133, 0.0722)
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Iteration: 80 (-563871.0723, 0.0699)
Iteration: 90 (-563860.8762, 0.0695)
Iteration: 100 (-563850.7625, 0.0691)
Group probs = (0.8131, 0.1544, 0.0324)

Outer iteration: 21
Iteration: 1 (-564732.5993, 0.1600)
Iteration: 10 (-564721.5529, 0.0689)
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Iteration: 100 (-564633.7056, 0.0654)
Group probs = (0.8157, 0.1512, 0.0330)

Outer iteration: 22
Iteration: 1 (-567390.7074, 0.2161)
Iteration: 10 (-567381.0945, 0.0648)
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Iteration: 100 (-567298.1318, 0.0621)
Group probs = (0.8190, 0.1477, 0.0333)

Outer iteration: 23
Iteration: 1 (-570700.3650, 0.3136)
Iteration: 10 (-570691.6425, 0.0619)
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Iteration: 100 (-570613.1782, 0.0592)
Group probs = (0.8202, 0.1458, 0.0341)

Outer iteration: 24
Iteration: 1 (-571759.4722, 0.4231)
Iteration: 10 (-571751.4565, 0.0586)
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Iteration: 100 (-571677.2661, 0.0563)
Group probs = (0.8220, 0.1435, 0.0345)

Outer iteration: 25
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Iteration: 10 (-573499.9480, 0.0568)
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Group probs = (0.8232, 0.1420, 0.0348)

Outer iteration: 26
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Iteration: 10 (-574676.8090, 0.0538)
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Iteration: 100 (-574608.7649, 0.0521)
Group probs = (0.8251, 0.1402, 0.0347)

Outer iteration: 27
Iteration: 1 (-576682.0282, 0.0955)
Iteration: 10 (-576675.1524, 0.0518)
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Group probs = (0.8266, 0.1387, 0.0346)

Outer iteration: 28
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Iteration: 10 (-578287.0621, 0.0501)
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Group probs = (0.8266, 0.1383, 0.0351)

Outer iteration: 29
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Group probs = (0.8269, 0.1379, 0.0352)

Outer iteration: 30
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Iteration: 100 (-578213.5805, 0.0453)
Group probs = (0.8263, 0.1379, 0.0358)

Outer iteration: 31
Iteration: 1 (-577382.9114, 0.1885)
Iteration: 10 (-577377.0589, 0.0453)
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Iteration: 100 (-577321.5499, 0.0439)
Group probs = (0.8269, 0.1375, 0.0356)

Outer iteration: 32
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Group probs = (0.8259, 0.1382, 0.0359)

Outer iteration: 33
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Iteration: 100 (-576775.3915, 0.0415)
Group probs = (0.8268, 0.1374, 0.0358)

Outer iteration: 34
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Group probs = (0.8278, 0.1366, 0.0356)

Outer iteration: 35
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Group probs = (0.8280, 0.1363, 0.0357)

Outer iteration: 36
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Group probs = (0.8283, 0.1361, 0.0356)

Outer iteration: 37
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Group probs = (0.8286, 0.1358, 0.0356)

Outer iteration: 38
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Group probs = (0.8269, 0.1369, 0.0362)

Outer iteration: 39
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Group probs = (0.8274, 0.1366, 0.0360)

Outer iteration: 40
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Outer iteration: 41
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Group probs = (0.8271, 0.1367, 0.0362)

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Group probs = (0.8281, 0.1361, 0.0358)

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Group probs = (0.8282, 0.1359, 0.0359)

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Group probs = (0.8264, 0.1366, 0.0370)

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Group probs = (0.8265, 0.1365, 0.0370)

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Group probs = (0.8266, 0.1364, 0.0370)

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Group probs = (0.8266, 0.1364, 0.0370)

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Group probs = (0.8265, 0.1365, 0.0371)

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Group probs = (0.8241, 0.1378, 0.0380)

20700.983 sec elapsed
Warning message:
In is.data.frame(x) : NAs introduced by coercion
> 
> # A little check...
> cor(resulting_data$x1, 
+     as.numeric(resulting_data$pid7), 
+     use="complete.obs")
[1] 0.4570099
Warning message:
In is.data.frame(y) : NAs introduced by coercion
>       
> # Save results...
> save(all_res, file="all_results_2d.RData")
> appended_data <- resulting_data %>%
+    # Merge addition survey variables back in
+    left_join(data %>% 
+                select(source, respondent, abb:local_economy),
+                by=c("source", "respondent")) 
> save(appended_data, file="bigsurveys_recoded_plus_estimates_2d.RData")
> 
> 
> 
> proc.time()
     user    system   elapsed 
66814.226  8896.678 76548.559 
